Search Results for author:
Found 9 papers, 0 papers with code
Diff4Steer: Steerable Diffusion Prior for Generative Music Retrieval with Semantic Guidance
Modern music retrieval systems often rely on fixed representations of user preferences, limiting their ability to capture users' diverse and uncertain retrieval needs.
PERSOMA: PERsonalized SOft ProMpt Adapter Architecture for Personalized Language Prompting
Understanding the nuances of a user's extensive interaction history is key to building accurate and personalized natural language systems that can adapt to evolving user preferences.
User Embedding Model for Personalized Language Prompting
Modeling long histories plays a pivotal role in enhancing recommendation systems, allowing to capture user's evolving preferences, resulting in more precise and personalized recommendations.
V2Meow: Meowing to the Visual Beat via Video-to-Music Generation
Video-to-music generation demands both a temporally localized high-quality listening experience and globally aligned video-acoustic signatures.
Multi-Task End-to-End Training Improves Conversational Recommendation
In this paper, we analyze the performance of a multitask end-to-end transformer model on the task of conversational recommendations, which aim to provide recommendations based on a user's explicit preferences expressed in dialogue.
MAQA: A Multimodal QA Benchmark for Negation
Multimodal learning can benefit from the representation power of pretrained Large Language Models (LLMs).
Mondegreen: A Post-Processing Solution to Speech Recognition Error Correction for Voice Search Queries
As more and more online search queries come from voice, automatic speech recognition becomes a key component to deliver relevant search results.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Zero-Shot Heterogeneous Transfer Learning from Recommender Systems to Cold-Start Search Retrieval
In light of these problems, we observed that most online content platforms have both a search and a recommender system that, while having heterogeneous input spaces, can be connected through their common output item space and a shared semantic representation.
A Bayesian Probability Calculus for Density Matrices
Finite probability distributions are a special case where the density matrix is restricted to be diagonal.
